RT Conference Proceedings
T1 A novel Torque Vectoring Algorithm with Regenerative Braking Capabilities
A1 Parra, Alberto
A1 Zubizarreta, Asier
A1 Perez, Joshue
AB Intelligent Transportation Systems (ITS) is currently one of the most active research areas, being electric vehicles (EVs) and their vehicle dynamics enhancement key topics. For this purpose, the development of optimal Advanced Driver-Assistance Systems (ADAS) and Advanced Vehicle Dynamics Control Systems (AVDC) is required. Conventionally, these systems have been focused on increasing the stability of the vehicle in critical scenarios. However, EVs enable the possibility of including also the efficiency by making use of the regenerative braking as a control variable. In order to be able to design such sophisticated control systems, it is necessary to implement control techniques capable to manage both stability and efficiency. In this sense, intelligent control techniques have demonstrated to be one of the best alternatives. In this work a Torque Vectoring (TV) algorithm based on intelligent control techniques and with regenerative braking capabilities is presented. The presented TV approach has been implemented in a embedded platform and tested in a Hardware in the Loop (HiL) setup. Results show that the presented approach is able to not only enhance the dynamics vehicle behaviour in a challenging emergency manoeuvre, but also to increase its overall efficiency.
PB IEEE Computer Society
SN 9781728148786
YR 2019
FD 2019-10
LK https://hdl.handle.net/11556/2571
UL https://hdl.handle.net/11556/2571
LA eng
NO Parra , A , Zubizarreta , A & Perez , J 2019 , A novel Torque Vectoring Algorithm with Regenerative Braking Capabilities . in Proceedings : IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society . , 8926644 , IECON Proceedings (Industrial Electronics Conference) , vol. 2019-October , IEEE Computer Society , pp. 2592-2597 , 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 , Lisbon , Portugal , 14/10/19 . https://doi.org/10.1109/IECON.2019.8926644
NO conference
NO Publisher Copyright: © 2019 IEEE.
NO Authors wants to thank to the ECSEL HIPERFORM Project (with grant number 783174) and to the H2020 ACHILES Project (with grant number 824311) for their support in the development of this work.
DS TECNALIA Publications
RD 29 jul 2024